Dispersion of relative importance values contributes to the ranking uncertainty: sensitivity analysis of Multiple Criteria Decision-Making methods
Multiple Criteria Decision-Making (MCDM) methods are widely used in research and industrial applications. These methods rely heavily on expert perceptions and are often sensitive to the assumptions made. The reliability and robustness of MCDM analysis can be further tested and verified by a computer...
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| Format: | Article |
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Elsevier
2018
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| Online Access: | https://eprints.nottingham.ac.uk/50528/ |
| _version_ | 1848798273895137280 |
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| author | Maliene, Vida Dixon-Gough, Robert Malys, Naglis |
| author_facet | Maliene, Vida Dixon-Gough, Robert Malys, Naglis |
| author_sort | Maliene, Vida |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Multiple Criteria Decision-Making (MCDM) methods are widely used in research and industrial applications. These methods rely heavily on expert perceptions and are often sensitive to the assumptions made. The reliability and robustness of MCDM analysis can be further tested and verified by a computer simulation and sensitivity analysis. In order to address this, five different MCDM approaches, including Weighted Sum Model (WSM), Weighted Product Model (WPM), revised Analytic Hierarchy Process (rAHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and COmplex PRoportional ASsessment (COPRAS) are explored in the paper. Real data of the case study for assessing housing affordability are used for testing the robustness of alternative ranking and finding the most sensitive criteria to the change of criterion weight. We identify the most critical criteria for any and best ranking alternatives. The paper highlights the significance of sensitivity analysis in assessing the robustness and reliability of MCDM outcomes. Furthermore, randomly generated and model-based data sets are used to establish relationship between the dispersion of relative importance values of alternatives and ranking uncertainty. Our findings demonstrate that the dispersion of relative importance values of alternatives correlate with the Euclidian distances of aggregated values. We conclude that the dispersion of relative importance values contributes directly to the ranking uncertainty and can be used as a measure for identifying critical criteria. |
| first_indexed | 2025-11-14T20:17:09Z |
| format | Article |
| id | nottingham-50528 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:17:09Z |
| publishDate | 2018 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-505282020-05-04T19:44:04Z https://eprints.nottingham.ac.uk/50528/ Dispersion of relative importance values contributes to the ranking uncertainty: sensitivity analysis of Multiple Criteria Decision-Making methods Maliene, Vida Dixon-Gough, Robert Malys, Naglis Multiple Criteria Decision-Making (MCDM) methods are widely used in research and industrial applications. These methods rely heavily on expert perceptions and are often sensitive to the assumptions made. The reliability and robustness of MCDM analysis can be further tested and verified by a computer simulation and sensitivity analysis. In order to address this, five different MCDM approaches, including Weighted Sum Model (WSM), Weighted Product Model (WPM), revised Analytic Hierarchy Process (rAHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and COmplex PRoportional ASsessment (COPRAS) are explored in the paper. Real data of the case study for assessing housing affordability are used for testing the robustness of alternative ranking and finding the most sensitive criteria to the change of criterion weight. We identify the most critical criteria for any and best ranking alternatives. The paper highlights the significance of sensitivity analysis in assessing the robustness and reliability of MCDM outcomes. Furthermore, randomly generated and model-based data sets are used to establish relationship between the dispersion of relative importance values of alternatives and ranking uncertainty. Our findings demonstrate that the dispersion of relative importance values of alternatives correlate with the Euclidian distances of aggregated values. We conclude that the dispersion of relative importance values contributes directly to the ranking uncertainty and can be used as a measure for identifying critical criteria. Elsevier 2018-06-30 Article PeerReviewed Maliene, Vida, Dixon-Gough, Robert and Malys, Naglis (2018) Dispersion of relative importance values contributes to the ranking uncertainty: sensitivity analysis of Multiple Criteria Decision-Making methods. Applied Soft Computing, 67 . pp. 286-298. ISSN 1568-4946 multiple criteria analysis sensitivity analysis robustness data dispersion housing affordability https://www.sciencedirect.com/science/article/pii/S1568494618301170 doi:10.1016/j.asoc.2018.03.003 doi:10.1016/j.asoc.2018.03.003 |
| spellingShingle | multiple criteria analysis sensitivity analysis robustness data dispersion housing affordability Maliene, Vida Dixon-Gough, Robert Malys, Naglis Dispersion of relative importance values contributes to the ranking uncertainty: sensitivity analysis of Multiple Criteria Decision-Making methods |
| title | Dispersion of relative importance values contributes to the ranking uncertainty: sensitivity analysis of Multiple Criteria Decision-Making methods |
| title_full | Dispersion of relative importance values contributes to the ranking uncertainty: sensitivity analysis of Multiple Criteria Decision-Making methods |
| title_fullStr | Dispersion of relative importance values contributes to the ranking uncertainty: sensitivity analysis of Multiple Criteria Decision-Making methods |
| title_full_unstemmed | Dispersion of relative importance values contributes to the ranking uncertainty: sensitivity analysis of Multiple Criteria Decision-Making methods |
| title_short | Dispersion of relative importance values contributes to the ranking uncertainty: sensitivity analysis of Multiple Criteria Decision-Making methods |
| title_sort | dispersion of relative importance values contributes to the ranking uncertainty: sensitivity analysis of multiple criteria decision-making methods |
| topic | multiple criteria analysis sensitivity analysis robustness data dispersion housing affordability |
| url | https://eprints.nottingham.ac.uk/50528/ https://eprints.nottingham.ac.uk/50528/ https://eprints.nottingham.ac.uk/50528/ |